Text-to-Image
Diffusers
diffusers-training
lora
template:sd-lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
Instructions to use Tonioesparza/ourhood_training_dreambooth_lora_2_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Tonioesparza/ourhood_training_dreambooth_lora_2_0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SG161222/RealVisXL_V5.0", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Tonioesparza/ourhood_training_dreambooth_lora_2_0") prompt = "A photograph, of an Ourhood privacy booth, front view, in a warehouse eventspace environment, in the style of event photography, silken oak frame, checkered warm grey exterior fabric, checkered warm grey interior fabric, curtains, diner seating, pillows" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 221982d2239cade57a02524769080faeead8f61ad82aa8eb4ae74e5d947b3244
- Size of remote file:
- 14.3 kB
- SHA256:
- 0b853f4b65d00f12c1b5af61698267009e3294e8308de46a97703f6423ce8a8a
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